Does high number of output labels affect the performance of BERT and how to handle the class imbalance issue while doing multi text classification?

[John6666]

He seems to have gotten the answer itself. It doesn’t seem easy to improve performance…

Does high number of output labels affect the performance of BERT and how to handle the class imbalance issue while doing multi text classification?

Most efficient multi-label classifier?

Background I’m trying to train a model in Tensorflow to classify text according to a fixed set of 5 labels. For example, let’s say I feed my model the following text: “my advice is that you go ahead with your plans to learn Python, because its syntax is easy for beginners. It’s also great for snake lovers like me!” After sniffing the text, the model would, ideally, report back how much the text matches my pre-defined labels: Label Prediction -------------------- -----…

GitHub - AjNavneet/BERT-Text-Classification-MultiClass: Multi-class text classification model using the...